Automated Artifact Removal in EEG Signals of Brain Computer Interface using Wavelets and ICA
Rajashekhar U1, Neelappa2, K.Viswanath3
1Rajashekhar U, Govt. Engineering College, Haveri Karnataka, India
2Dr.Neelappa, Govt. Engineering College, Kushalnagar, Karnataka, India.
3Dr.K.Viswanath, Professor & Head, Dept. of ECE, R.L.Jalappa Institute of Technology, Bangalore.
Manuscript received on September 18, 2019. | Revised Manuscript received on 27 September, 2019. | Manuscript published on October 10, 2019. | PP: 896-907 | Volume-8 Issue-12, October 2019. | Retrieval Number: J90680981119/2019©BEIESP | DOI: 10.35940/ijitee.J9068.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A brain-computer interface (BCI) gives a correspondence channel that interconnects the mind with an outside device. The most generally utilized system for getting BCI control signals from the brain is the electroencephalogram (EEG). In the proposed paper, BCI framework towards an EEG chronicles are reviewed into and found that the expansion of a counterfeit motion toward it, which is brought about by eye flickers, eye development, muscle and cardiovascular commotion, just as non-natural sources (e.g., control line clamor). According to the writing survey it is discovered that these issues can be overwhelmed by utilizing mix of wavelet deterioration, independent component analysis (ICA), and thresholding.
Keywords: Automated Artifacts Removal, ICA, BSS, MSSA, Wavelet Transform.
Scope of the Article: Aggregation, Integration, and Transformation